Date of Award:
5-2018
Document Type:
Dissertation
Degree Name:
Doctor of Philosophy (PhD)
Department:
Computer Science
Committee Chair(s)
Stephen W. Clyde
Committee
Stephen W. Clyde
Committee
Vicki H. Allan
Committee
Curtis Dyreson
Committee
Haitao Wang
Committee
Qingyang Hu
Abstract
There are high demands of effective and high-performance of collaborations between mobile devices in the places where traditional Internet connections are unavailable, unreliable, or significantly overburdened, such as on a battlefield, disaster zones, isolated rural areas, or crowded public venues. To enable collaboration among the devices in opportunistic networks, code offloading and Remote Method Invocation are the two major mechanisms to ensure code portions of applications are successfully transmitted to and executed on the remote platforms. Although these domains are highly enjoyed in research for a decade, the limitations of multi-device connectivity, system error handling or cross platform compatibility prohibit these technologies from being broadly applied in the mobile industry.
To address the above problems, we designed and developed UMSEF - an Universal Mobile Service Execution Framework, which is an innovative and radical approach for mobile computing in opportunistic networks. Our solution is built as a component-based mobile middleware architecture that is flexible and adaptive with multiple network topologies, tolerant for network errors and compatible for multiple platforms. We provided an effective algorithm to estimate the resource availability of a device for higher performance and energy consumption and a novel platform for mobile remote method invocation based on declarative annotations over multi-group device networks. The experiments in reality exposes our approach not only achieve the better performance and energy consumption, but can be extended to large-scaled ubiquitous or IoT systems.
Checksum
6d81ef01a774c054b69487ff8a3e5697
Recommended Citation
Le, Minh, "Universal Mobile Service Execution Framework for Device-To-Device Collaborations" (2018). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 7032.
https://digitalcommons.usu.edu/etd/7032
Included in
Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .